If a `file_pattern` matches several files, `preferred_shard` can be used to hint
in which file the requested tensor is likely to be found. This op will first
open the file at index `preferred_shard` in the list of matching files and try
to restore tensors from that file.  Only if some tensors or tensor slices are
not found in that first file, then the Op opens all the files. Setting

    "LESS",
    "NEG",
    "PADV2",
    "GREATER",
    "GREATER_EQUAL",
    "LESS_EQUAL",
    "SELECT",
    "SLICE",
    "SIN",
    "TRANSPOSE_CONV",
    "SPARSE_TO_DENSE",
    "TILE",
    "EXPAND_DIMS",
    "EQUAL",
    "NOT_EQUAL",
    "LOG",
    "SUM",
    "SQRT",
    "RSQRT",
    "SHAPE",
    "POW",
    "ARG_MIN",
    "FAKE_QUANT",
    "REDUCE_PROD",

                            "title": "End Datetime",
                            "type": "string",
                            "format": "date-time",
                        },
                        "repeat_at": IsDict(
                            {
                                "title": "Repeat At",
                                "anyOf": [
                                    {"type": "string", "format": "time"},

    path = tmp_path / "test.txt"
    path.write_bytes(b"<file content>")
    path2 = tmp_path / "test2.txt"
    path2.write_bytes(b"<file content2>")

    client = TestClient(app)
    with path.open("rb") as file, path2.open("rb") as file2:
        response = client.post(
            "/files/",
            files=(
                ("files", ("test.txt", file)),
                ("files", ("test2.txt", file2)),
            ),

                            "title": "End Datetime",
                            "type": "string",
                            "format": "date-time",
                        },
                        "repeat_at": IsDict(
                            {
                                "title": "Repeat At",
                                "anyOf": [
                                    {"type": "string", "format": "time"},

			{{$Goroutine := .}}
			{{range $.NonOverlappingStats}}
				{{$Time := index $Goroutine.NonOverlappingStats .}}
				{{if $Time}}
					<span {{barStyle . $Time $.MaxTotal}}>&nbsp;</span>
				{{end}}
			{{end}}
			</div>
		</td>
		{{$Goroutine := .}}
		{{range $.NonOverlappingStats}}
			{{$Time := index $Goroutine.NonOverlappingStats .}}
			<td> {{$Time.String}}</td>
		{{end}}
	</tr>
{{end}}
</table>

// license that can be found in the LICENSE file.

// Simple file i/o and string manipulation, to avoid
// depending on strconv and bufio and strings.

package net

import (
	"internal/bytealg"
	"io"
	"os"
	"time"
)

type file struct {
	file  *os.File
	data  []byte
	atEOF bool
}

func (f *file) close() { f.file.Close() }

func (f *file) getLineFromData() (s string, ok bool) {
	data := f.data

func TestEmbeddedPointerTypeStruct(t *testing.T) {
	type BasePost struct {
		Id    int64
		Title string
		URL   string
	}

	type Author struct {
		ID          string
		Name        string
		Email       string
		Age         int
		Content     Content
		ContentPtr  *Content
		Birthday    time.Time
		BirthdayPtr *time.Time
	}

	type HNPost struct {
		*BasePost
		Upvotes int32

	}
	if i := strings.Index(file, "/"); i >= 0 {
		bad = append(bad,
			file[:i]+"//"+file[i+1:],
			file[:i]+"/./"+file[i+1:],
			file[:i]+`\`+file[i+1:],
			file[:i]+"/../"+file,
		)
	}
	if i := strings.LastIndex(file, "/"); i >= 0 {
		bad = append(bad,
			file[:i]+"//"+file[i+1:],
			file[:i]+"/./"+file[i+1:],
			file[:i]+`\`+file[i+1:],
			file+"/../"+file[i+1:],
		)
	}

	for _, test := range []struct {
		window time.Duration
		want   float64
		worst  []float64
	}{
		{0, 0, []float64{}},
		{time.Millisecond, 0, []float64{0, 0}},
		{time.Second, 0, []float64{0, 0}},
		{2 * time.Second, 0.5, []float64{0.5, 0.5}},
		{3 * time.Second, 1 / 3.0, []float64{1 / 3.0}},
		{4 * time.Second, 0.5, []float64{0.5}},
		{5 * time.Second, 3 / 5.0, []float64{3 / 5.0}},
		{6 * time.Second, 3 / 5.0, []float64{3 / 5.0}},
	} {